Dr. Maria Aránzazu Sulé Alonso Faculty
December 19, 2021
Dr. Andy HoggFaculty
December 20, 2021
Dr. K. Ravindranath Tagore
Faculty
Dr. K. Ravindranath Tagore is a highly regardable educator with a doctorate in Computer Science and Engineering. His expertise lies in Artificial Intelligence and its applications in engineering. At EIIET, he applies his education in teaching undergraduate and postgraduate students various aspects of computing such as Machine Learning, Deep Learning, Data Science, and Cyber Security. He adopts a dynamic, engaging and above all a student-oriented approach to teaching these students.
Dr. Ravindranath believes in a practical application approach. He utilizes real-world industry projects and problems to explain the foundations of various concepts. His deep knowledge of industry standards and various tools, such as Python, Power BI, and Azure Data Factory, ensures that he is able to introduce the students to projects and tools that are relevant and assists them in accomplishing their objectives.
Dr. Ravindranath balances his teaching duties with an active research career in Artificial Neural Networks and their applications in engineering. His current focus is on industrial classification systems and Deep Learning-based pattern recognition. He has a number of research publications in highly regarded journals. He continues to research to enhance his teaching and introduce various contemporary concepts into the existing curriculum.
He shows a strong interest in the development of students beyond just the formal teaching that takes place in a classroom. He takes mentorship seriously, having assisted many undergraduate and postgraduate students in the preparation of their projects and theses. He gives mentorship that is constructive and is informed by a combination of theoretical and practical knowledge. He brings that same level of dedication to curriculum design and to the quality assurance processes of the institution. This dedication to scholarship creates a high level of professional standard for the institution and its employees.
Qualitative teaching is not separated from qualitative research. This is the philosophy of Dr. Ravindranath. He is an active participant in faculty development workshops and seminars/academic conferences. He is up to date with the current trends of research and practice in AI and related technologies. This scholarship is a requirement of his position. It is the belief of Dr. Ravindranath that good quality teaching and research that is also good is synergistic and positively impacts the students of the institution.
Publications
Journal Publications
- “Integration of Machine Learning Based Advanced Neural Networks for Various Applications”, published in International Journal of Advanced Technology and Engineering Exploration (Paper ID: IJATEE_1/25_212535), 2026, ISSN: 2394-5443, Q3 (1.6842)/2.7, indexed in Scopus, Google Scholar, and listed in the UGC Care List.
- “Deep Learning Approaches for the Classification of Diesel Injector Spray Pattern”, published in International Journal of Information Technology & Computer Engineering, Vol-13, Issue-1, 2025, pp. 789–795, ISSN: 2347-3657, DOI Prefix: 10.62647, Impact Factor: 6.091, indexed in CROSSREF, ROAD, and THE KEEPERS, and listed in the UGC Care List.
- “Information Retrival and Summerizing of Documents Using Artificial Neural Networks”, published in Res Militaris, Social Science Journal, Vol-13, Issue-3, 2023, pp. 6206–6213, ISSN: 2265-6294, Q4 / 0.102 SJR, listed as a peer-reviewed academic journal in the UGC Care List.nal in the UGC Care List.
- “Automated Diesel Spray Classification Using Convolution Neural Networks”, published in Journal of Computational Analysis and Applications, Vol-33, Issue-7, 2024, pp. 1828–1835, ISSN: 1521-1398, Q3 / 2.82, indexed in Scopus and databases including EBSCO.
- “Global Optimization Technics for Training Feed Forward Neural Networks in Forecasting Applications”, published in Journal of Engineering Sciences, Vol-14, Issue-4, 2023, pp. 1666–1678, ISSN: 0377-9254, Impact Factor: 6.54, listed as a peer-reviewed academic journal in the UGC Care List.
Book Publications
- “Deep Learning Approaches for the Classification of Diesel Injector Spray Pattern”, published in the proceedings of the 4th International Conference on Innovation and Recent Trends in Computer Science (ICIRTCS-2024), Hyderabad, 2024, ISBN: 978-93-94246-59-1, published by St. Martin’s College of Engineering.
- “Global Optimization Techniques for Training Feed-Forward Neural Networks”, published in the proceedings of the 2nd International Conference on Innovation and Recent Trends in Computer Science (ICIRTCS-2023), Hyderabad, 2023, ISBN: 978-93-91420-22-2, published by St. Martin’s College of Engineering.